Call for Paper - October 2019 Edition
IJCA solicits original research papers for the October 2019 Edition. Last date of manuscript submission is September 20, 2019. Read More

Prognosis of Heart Disease using Data Mining Techniques: A Comprehensive Survey

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Ankita Naik, Nitesh Naik

Ankita Naik and Nitesh Naik. Prognosis of Heart Disease using Data Mining Techniques: A Comprehensive Survey. International Journal of Computer Applications 181(17):14-18, September 2018. BibTeX

	author = {Ankita Naik and Nitesh Naik},
	title = {Prognosis of Heart Disease using Data Mining Techniques: A Comprehensive Survey},
	journal = {International Journal of Computer Applications},
	issue_date = {September 2018},
	volume = {181},
	number = {17},
	month = {Sep},
	year = {2018},
	issn = {0975-8887},
	pages = {14-18},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2018917765},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Prediction and diagnosis of heart disease has become a formidable factor faced by medical practitioners and hospitals both in India and also worldwide. The early and timely diagnosis of heart disease plays a very crucial role in halting its advancement and reducing related medical costs. Taking into account the ever-increasing rise in heart disease-induced mortality, different techniques have been adopted to treat it. The idea intends to develop a heart disease prediction model, which will implement ensemble techniques, can help the doctors in detecting the heart disease status based on the patient's clinical data. This paper provides a quick and facile analysis and understanding of available prediction models using data mining from 2011 to 2017. The comparison shows the accuracy level of each model given by different researchers.


  1. Randa El Bialy, Mostafa A. Salama, Omar karam. 2016. An ensemble model for Heart disease data sets: a generalized model, ACM May 2016.
  2. Mai Shouman, Tim Turner, Rob Stocker ,“Using Decision Tree for Diagnosing Heart Disease Patients , ACM,2011.
  3. Purushottama , Prof. (Dr.) Kanak Saxena, Richa Sharma “Efficient Heart Disease Prediction System”, Elsevier ,2016.
  4. Ilayaraja M, Meyyappan T , “ Efficient Data Mining Method to Predict the Risk of Heart Diseases through Frequent Itemsets”, Elsevier 2016.
  5. Theresa Princy ,J. Thomas “Human Heart Disease Prediction System using Data Mining Techniques” ,IEEE ,2016.
  6. Shan Xu ,Zhen Zhang, Daoxian Wang, Junfeng Hu, Xiaohui , “Cardiovascular Risk Prediction Method Based on CFS Subset Evaluation and Random Forest Classification Framework” ,IEEE 2017 .
  7. Hlaudi Daniel Masethe, Mosima Anna Masethe , “Prediction of Heart Disease using Classification Algorithms”, Vol II WCECS 2014, 22-24 October, 2014, San Francisco, USA.
  8. S Radhimeenakshi , “Classification and prediction of heart disease risk using data mining techniques of support vector machine and artificial neural networks” ,IEEE, 2016.
  9. Ritika Chadha ,Shubhankar Mayank , “Prediction of heart disease using data mining techniques” ,Springer , December2016.
  10. Aigerim Altayeva , żSuleimenov Zharas ,Young Im Cho “Medical Decision Making Diagnosis System Integrating k-means and Naïve Bayes algorithms” , IEEE October 2016.
  11. B.Venkatalakshmi, M.V Shivsankar, “Heart disease diagnosis using predictive data mining”, ICIET, March 2014.
  12. Jagdeep Singh, Amit Kamra, Harbhag Singh , “Prediction of Heart Diseases Using Associative Classification” ,IEEE ,2016.
  13. Saba Bashir, Usman Qamar, M.Younus Javed, “An Ensemble based Decision Support Framework for Intelligent Heart Disease Diagnosis” ,IEEE 2014.
  14. =5176.100239.blogcont54260.8.TRNGoO
  15. Shamsher Bahadur Patel, Pramod Kumar Yadav and Dr. D.P. Shukla, “Predict the Diagnosis of Heart Disease Patients using classification Mining Techniques”, IOSR Journal of Agriculture and Veterinary Science (IOSR-JAVS), 2013.
  16. I.S.Jenzi, P.Priyanka, Dr.P.Alli, “A Reliable Classifier Model Using Data Mining Approach for Heart Disease Prediction”, International Journal of Advanced Research in Computer Science and Software Engineering, 2013.
  17. Lokanath Sarangi, Mihir Narayan Mohanty, Srikanta Pattnaik, “An Intelligent Decision Support System for Cardiac Disease Detection”, IJCTA, International Press 2015.
  18. Chaitrali S. Dangare Sulabha S Apte, “Improve study of Heart Disease prediction system using Data Mining Classification techniques”, International journal of computer application, 2012.
  19. Luo Y, Li Z, Guo H, Cao H, SongC, Guo X, et al..,Predicting congenital heart defects: A comparison of three data mining methods.PLoS ONE 12(5):e0177811,2017.
  20. Mai Shouman, Tim Turner, Rob Stocker, “ Using data mining techniques in heart disease diagnosis and treatment”, IEEE Japan-Egypt Conference on Electronics, Communications and Computers, 2012.


Prediction, heart disease, classification, ensemble, diagnosis